Expression of caveolin-1 in breast cancer stroma as a potential prognostic biomarker of survival and progression: a meta-analysis.

Abstract

BACKGROUND:

It has been shown that caveolin-1 plays a potential role as a diagnostic and prognostic biomarker in various cancer types. The aim of the present study was to clarify whether caveolin-1 expressed in the breast cancer stroma could be a prognostic factor for breast cancer patients.

METHODS:

We searched the PubMed, ScienceDirect and Web of Science databases for published literature investigating associations between stromal caveolin-1 expression and survival outcome in breast cancer patients. With respect to survival outcomes, the pooled hazard ratios (HRs) of caveolin-1 and the 95% confidence intervals (CI) were calculated.

RESULTS:

Our meta-analysis identified a total of 10 studies involving 2072 cases. Further investigation demonstrated that a lack of caveolin-1 expression in the breast cancer stroma is a hazard for overall survival (OS) (HR = 2.33, 95% CI: 1.57-3.46) and disease-free/progression-free survival (DFS/PFS) (HR = 3.05, 95% CI: 2.26-4.12) in breast cancer patients. Moreover, lack of caveolin-1 expression in the cancer-associated fibroblasts was a significant predictor of DFS/PFS (HR = 2.79, 95% CI: 1.75-4.46).

CONCLUSION:

Our results indicated that lack of expression of caveolin-1 in the breast cancer stroma is associated with a poor prognosis.

• Authors: Xiuying Li, Jinfan Sun, Shuenqin Hu
• Journal: Wiener klinische Wochenschrift (Wien Klin Wochenschr) Vol. 129 Issue 15-16 Pg. 558-563 (Aug 2017) ISSN: 1613-7671 [Electronic] Austria
• PMID: 28364168 (Publication Type: Journal Article, Meta-Analysis)

Chemical References

• Biomarkers, Tumor
• Caveolin 1

Topics

• Biomarkers, Tumor (genetics)
• Breast (pathology)
• Breast Neoplasms (diagnosis, genetics, mortality, pathology)
• Caveolin 1 (genetics)
• Confidence Intervals
• Correlation of Data
• Female
• Fibroblasts (pathology)
• Follow-Up Studies
• Humans
• Kaplan-Meier Estimate
• Mesoderm (pathology)
• Middle Aged
• Prognosis
• Proportional Hazards Models